Automatic Determination Number of Cluster for NMKFC-MeansAlgorithms on Image Segmentation
Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2015, Vol 17, Issue 1
Abstract
Abstract: Image segmentation plays an important role in image analysis. Image segmentation is useful in manyapplications like medical, face recognition, crop disease detection, and geographical object detection in map.Image segmentation is performed by clustering method. Clustering method is divided into Crisp and Fuzzyclustering methods. FCM is famous method used in fuzzy clustering to improve result of image segmentation.FCM does not work properly in noisy and nonlinear separable image, to overcome this drawback, KFCMmethod for image segmentation can be used. In KFCM method, Gaussian kernel function is used to convertnonlinear separable data into linear separable data and high dimensional data and then apply FCM on thisdata. KFCM is improving result of noisy image segmentation. KFCM improves accuracy rate but does not focuson neighbor pixel. NMKFCM method incorporates neighborhood pixel information into objective function andimproves result of image segmentation. New proposed algorithm is effective and efficient than other fuzzyclustering algorithms and it has better performance in noisy and noiseless images. In noisy image, findautomatically required number of cluster with the help of Hill-climbing algorithm
Authors and Affiliations
Pradip M. Paithane , Prof. S. A. Kinariwala
Keywords
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